The study seeks to develop a better understanding of the unique drivers and barriers encountered by Dutch Deep-Tech Startups (DTS) in the Sustainable Energy (SE) sector during their pre-founding to founding stages. The aim is to identify effective strategies employed by entrepreneurs to navigate these challenges and to leverage the drivers. Despite their potential to address major societal challenges, these startups often face high failure rates due to inherent complexities and dependence on heavy R&D. To gain a better understanding of the drivers, barriers, and strategies, the study utilizes literature review and semi-structured interviews. Key findings highlight supportive academic culture, regulatory environment (RE), business networks, entrepreneurial factors, and personal motivations as drivers, while identifying barriers such as academic-commercial divergence, regulatory complexity, investor discrepancies, entrepreneurial factors, market research (MR) challenges and personal barriers. Strategies for success include forming cross-disciplinary teams, leveraging academic resources, strategic funding opportunities, adapting to market needs, and maintaining resilience and motivation. A conceptual framework is proposed to guide future entrepreneurs.
The study aims to benefit future DTS entrepreneurs, by offering practical strategies and insights for overcoming barriers and leveraging drivers. Besides DTS entrepreneurs, the study also provides valuable insights for universities and policymakers. The research offers policymakers insights on optimizing the regulatory environment to better support DTS. It suggests the need for streamlined regulations and targeted funding initiatives. For universities, the findings highlight the importance of embracing an entrepreneurial culture and providing support systems for DTS, including access to specialized resources and mentorship programs. Overall, the study contributes to a deeper understanding of the factors that influence the success and failure of DTS, offering practical recommendations for enhancing their viability and impact.

All around the world projects are being developed as part of the move to more renewable systems of energy production and consumption, also known as the renewable energy transition. As global temperatures are reaching record levels there is an urgency to speed up progress. Unfortunately, numbers show that renewable energy developments are lagging behind and renewable energy ambitions on national levels are insufficient.

The realization of renewable energy transitions worldwide is not purely a technical affair – the use of new technologies by society comes with many challenges. For example, energy systems based on renewable energy become more decentralized compared to large-scale central energy production based on fossil resources. Renewable energy infrastructures are often large, technically complex installations with both social and environmental impact. This means that shifts in energy infrastructure have a substantial impact on our society, lifestyles and living environment. As a consequence of these changes and processes public conflict often occurs. Renewable energy controversies are a common part of renewable energy transitions.

Renewable energy controversies are social conflicts that articulate the values that are at stake for actors affected by new energy development, such as the establishment of a new location for wind turbines. As a controversy develops it reveals (hidden) social dimensions of the development and shows societal and ethical risks, costs and benefits that might have been unanticipated. The values that lead to conflict can concern the energy technology in question, the decision-making procedures or to those involved in or organizing these processes. As such, controversies can also be seen as a form of political engagement that has democratic value.

Conflicts over the planning and development of renewable energy and infrastructure, such as on- and offshore wind, solar, green hydrogen, geothermal, and transmission lines have been prominent over the past decades. These renewable energy controversies emerge when citizens, local residents, action groups or other stakeholders oppose plans or developments. Many controversies have resulted in delay or cancellation of projects. Controversies often end in unconstructive outcomes such as lengthy legal battles between project promoters and the challengers. As ongoing policy and societal efforts are put in effect to advance the global energy transition, it is likely that they will continue to arise in the years to come. As controversies are not a temporary phenomenon, but occur again and again, there is a need for better understanding controversies as well as searching for constructive ways to deal with them - especially given their democratic value.16

Controversies have three general characteristics: (1) they are publicly salient meaning they take place in the public sphere, are covered in the media and have peaks in which the conflict heats up; (2) controversies are complex and dynamic as they involve a multitude of actors and issues which often change over time. Conflicts from the past, in other places or on other technologies can also become intertwined with or fuel renewable energy controversies; and (3) controversies consist of a series of discursive interactions: project developers, government representatives, local residents, the general public, NGO’s and other stakeholders communicate and engage with each other in some kind of way. This means that the language used can be a starting point for further understanding.

These three characteristics reveal the strong relational nature of controversies. They comprise a cycle of interactions between a wide range of actors involved, their expectations of others feeding into engagement strategies and actions, which in turn shape interactions, and so on.

Over the past decades, renewable energy controversies have been widely studied by social science researchers from a variety of fields. The dominant approach here has been to approach controversies as lack of social acceptance, and renewable energy technology (RET) in need of social acceptance, which revolves around attitudes to and engagement with renewable energy technologies and infrastructure. In general, most research focuses on opposition or support of the general public, local residents and communities.

Despite the ongoing attention and developments in research focus within this field since the 80s, the investigation of renewable energy controversies generally (still) revolves around the perspectives, actions and experiences of the general public, local communities and opponents. This has resulted in the neglect of other important stakeholders involved in the development of renewable energy.

This dissertation seeks to address this important gap by focusing on the category of people representing organisations working on or supporting the renewable energy projects themselves in the context of renewable energy controversies. These actors are known as renewable energy technology actors (RET actors). The category of RET actors includes the project developers, their CEOs, engineers and communications managers, the consultants that are hired, trade associations as well as manufacturers and financiers of energy technologies. RET actors can be both private and public actors: depending on their role in projects, governments can be RET actors as well...
@en

Urban areas are highly dependent on their urban water systems, which provide essential services such as access to clean drinking water, public health protection, and flood control. Global developments increasingly threaten the provision of these services: changing weather patterns, ongoing urbanization processes, and depleting natural resources lead to environmental and public health issues, and increase the risk of urban flooding.

While traditional urban water systems (i.e., centralized water supply systems, sewer networks, and large-scale wastewater treatment facilities) have significantly contributed to global public health and protected cities from flooding, they are ill-equipped in the face of emerging global developments. For example, traditional systems have a limited ability to cope with extreme climate conditions, have a high net energy consumption, and lead to the deterioration of the environmental quality....@en

With the new Environment & Planning Act (Omgevingswet) planned to come into force on the 1^st of July 2023, citizen participation is currently relevant in the Dutch public debate. The Association of Dutch Municipalities (Vereniging Nederlandse Gemeenten) deems citizen participation as important because it enables a comprehensive consideration of interests and perspectives. Moreover, it is expected to prevent delays of juridical procedures in the realisation phase of a project. However, the implementation of the new Environment & Planning Act is the responsibility of the government authorities. One governing body struggling with the implementation of citizen participation is the Dutch province of Utrecht, together with its municipalities. The province of Utrecht wants to develop public transport nodes (PTNs). To be able to help municipalities with citizen participation the province has the desire to understand how citizens can best be involved in the development of public transport nodes (PTNs). Scholars studied the participation preferences of citizens, but two shortcomings were identified for the case of PTN development. Firstly, these studies took place in a different context than the context of PTN development. Secondly, these studies examined how citizens themselves want to participate, not how citizens think the government should let citizens participate. Both factors were expected to influence the participation preferences of citizens.
This problem background, the corresponding scope, and knowledge gap lead to the main research question of this study: How do citizens weigh different attributes of citizen participation regarding the policy-making process by the province of Utrecht in the context of public transport node development?

The main method to answer this research question is a discrete choice experiment (DCE). Firstly, literature research was conducted to identify relevant attributes of citizen participation. This resulted in five attributes: the Participation Moment, the Participation Selection Method, the Mode of Participation, the Extent of Influence, and the Costs. The literature research also established the preliminary levels of all except the Costs attribute. Secondly, to establish the final levels semistructured interviews were conducted with nine policymakers and civil servants. To establish the levels of the Costs attribute market research was conducted. Nine companies specialised in citizen participation were contacted. Ultimately, the levels of the Costs attribute were based on the information of one company but were verified by public sources and interview results. Thirdly, the information from the literature research, interviews, and market research was synthesised. Furthermore, for all except the Costs attribute, level descriptions were developed which explained the level and, if applicable, suited it to the case of PTN development. Fifthly, a survey was developed which included an opening statement, an introduction to the attributes and levels, ten choice sets with two participation scenarios and one No Participation scenario, and eight closing questions about demographics. In the choice sets, respondents were asked which participation scenario they would prefer for the province of Utrecht to choose...

With the rise of data, many sectors have been implementing a form of automatising in recent times. This brings a lot of possibilities. As a matter of fact, an automated system is – unlike the human brain – not dependent on food nor sleep and less prone to errors. The efficiencies that could be gained by ‘working’ 24 hours, 7 days a week without a single moment of pause is enormous. An Artificial Intelligence system (hereinafter: AI system) could provide a relief for many sectors. In the literature, the application for an AI system within the judicial system has been advocated for. Nevertheless, the judicial system, especially regarding the rights of a suspect, needs many more considerations than the workload-relief argument alone. In this thesis, the possible implementation of AI – or a robot judge – within the Dutch judicial system will be explored. In this research, a special focus will be given to the rights of a suspect as set out in article 6 of the European Convention on Human Rights (hereinafter: ECHR). Article 6 ECHR provides the right of a fair trial to a suspect, where relevant, with the following provision: “In the determination of his civil rights and obligations or of any criminal charge against him, everyone is entitled to a fair and public hearing within a reasonable time by an independent and impartial tribunal established by law”. From clause 1 of article 6 ECHR, the following components can be extracted: a fair, independent and impartial tribunal. Implicitly, article 6 ECHR also provides the right to an explanation on how this tribunal reached to its verdict. In practice, this is also referred to as the right to transparent verdicts. With the use of the research question “to what extent can Artificial Intelligence be used in the Dutch courtroom while still maintaining the rights for the parties involved, especially as how has been set out in article 6 ECHR?”, an answer is formulated on the question whether the Dutch judicial system is ready for – and capable of – the next judge: a robot judge. This research uses a systematic literature review as a starting point. With such review, information is gathered from both technical as well as legal point of views to answer each sub-question individually. This research also specifically looks at the way other countries have implemented or created a form of an AI tool in and as court. Next to this, four interviews have been held with potential stakeholders as well as persons of interest. The reason why these interviews are held is to confirm and check what has been found from the literature assessment as well as to gain new (internal) insights on this topic. As an answer to this research question, an AI system can be implemented in the Dutch courtroom if it consists of two (main) components: a linguistic system and a machine learning system. Additional rules to use this robot judge are proposed as well, for example that continuous feedback-loops (of the probabilities for example) should be built in and that the system should be continuously monitored (and adjusted) for potential biases. The robot judge can both function as and in court. Additionally, a robot judge can sit at the table of the Dutch Council for the Judiciary and their ambitions to (further) litigate digitally and publish more, if not all, cases online.

The Dutch rail sector is one of the most heavily used rail networks in Europe. It plays a critical role in the domestic transportation of passengers. Disruptions in the operation of one organisation can have a cascading effect on others within the sector. Risk management needs to identify and address these weaknesses to prevent largescale disruptions. The risks a rail organisation faces are diverse, ranging from financial risks to strategic risks. The enterprise risk management methodology addresses all the risks of an organisation to reduce the negative effect and seize opportunities. In recent years, there has been increased emphasis on data-driven work, including within the risk management domain. This research explores the implementation of data-driven work in the enterprise risk management of the Dutch passenger transporting rail sector. This research uses a comparative case study to explore the novel research field. The case study data is collected from interviews and desk research. This research concludes that datadriven
work adds value to the enterprise risk management of Dutch rail organisations. Data-driven enterprise risk management improves the predictive capabilities of rail organisations. In addition, it enables real-time monitoring of risks. Hence, it supports the decision-making process more precisely and accurately.

Scandals in which governmental ADM tools played a role, have recently brought
about political and societal debate about the potential harms to citizens that such automated systems potentially bring. This thesis focuses on ADM systems which contain an AI component. Based on the knowledge gaps perceived,
the main research question for this study is: In public sector AI systems, what are emerging vulnerabilities for citizens and how do these translate into
governance requirements for decision-makers? The approach to answer this question is an adjusted form of Theory Building from Case Study. A layered ’onion model’ presents four relevant contexts to consider for AI System vulnerabilities specifically in the public sector: AI model, Model deployment, Political-administrative, and Societal. The case study results demonstrate that dealing with vulnerabilities in one of the four model contexts often complicates dealing with vulnerabilities in the other contexts. Hence, the vulnerabilities model points to so-called governance requirements dilemmas.

A lack of understanding of ecosystem-related projects and scarcity of natural capital reimbursement mechanisms leads to passive involvement and hesitation from the private sector when investing in nature. This study conducts a systematic literature review, furnishes a database of the relevant barriers and drivers for the private investment in Nature-Based Solutions, and using Bayesian Belief Networks builds a probabilistic graphical model of a real case.

The use of Open Data (OD) in an Engineering Asset Management (EAM) context is largely unexplored. Even though research into OD is moving forward, this knowledge is not fully usable in EAM because of the complexity and the specific characteristics of EAM. The research is centred around the case study that has taken place. As input for the case study, a literature review has been conducted to summarize and analyse the existing knowledge of OD and EAM. This created a starting point for the case study. A case about the traffic situation around the IJsselbruggen and the VIA15 project (A12) has been selected to research the possibilities to use OD with the goal to evaluate the current traffic measures and investigate the possibilities for Data-Driven Decision Making (DDDM). The combined results of the literature review and the case study have been reviewed by a group of experts in an expert workshop session. Besides there critical opinion about the research, the experts where also asked about their view on the use of OD in the EAM sector.

To provide insight into factors that play a role for DT in the humanitarian sector, a combination of literature and expert interviews was used to identify relevant criteria for the humanitarian sector. In accordance with prevailing literature, these factors have been categorised in people, process and technology factors. People factors include leadership, human resources, culture, organisational structure. Process factors were: alignment operations & IT, long term commitment Management, long term commitment network, long term commitment donor, crisis response, Legal issues. Finally, technology factors included both data and digital. The identified critical DT factors were translated into an assessment framework making use of the CMMi Maturity Model approach. For each factor and maturity level combination, there is an explanation of what a humanitarian organisation has to comply with, before advancing to the next level. This ensures that national societies can generate an overview where they currently are and what steps to take to advance. To adequately deal with the barriers and increase practical applicability of the framework, separate barrier-overcoming-strategies have been formulated.

What happens when we treat our policy messages more like mythology and less like rhetoric? How can we even begin to structure policy as a mythology? What is a myth anyway? This thesis endeavors to explore the mysterious world of stories, through an extensive literature review of literary analysis, and a exemplary case study about the impact of global plastics production on the future. This study leads to an experiment, where four different forms of communication: the best of rhetoric and stories, are tested against each other for effectiveness in shifting the mood, transferring information, and effecting the audience's experience. The results show that even with a small sample size the impact of stories as effective tools of policy communication are real. They result in a drastically different message than the other forms tested, hinting at the possibility of a future where stories are central to shaping policy.

In this report the potential effect of framing on the decision-making process in participatory value evaluation is researched. Participatory Value Evaluation, PVE, is a method of evaluating citizens preference targeted towards public projects and their budget. For instance, PVE can measure the preference of citizens when allocating alternative infrastructure projects with a set budgetA gap in knowledge is found in the decision-making process of the method. The validity of participatory value evaluation is potentially affected by cognitive bias effects such as framing. The main question of this research is: Is there a measurable difference in outcome of the decision-making process between emphasis-framed alternatives within the participatory value evaluation method? The used method is a between-subject design, laboratory experiment. Three versions of the same basic PVE are constructed. A control version with neutral descriptions of the potential projects, and two framed versions through the structure of one-sided emphasis framing. A convenience sample of 181 participants is used, with each version of the PVE receiving roughly 60 participants. The three versions of the PVE were kept exactly the same with exception of the framed descriptions. A difference between the groups is shown to be significant on a project level in six out of six tested projects. Concluded is that, in general, emphasis-framing has an effect on the decision-making in PVE. The effect of framing is argued to have a limitation. When participants feel strongly about a certain topic, the frame influences the outcome less, this is known as issue importance. Recommendations to further research are made, as a method for mitigating the influence within PVE can be researched. The impact of overall presentation of different projects, in terms of framing with images, or extensive project descriptions, can be researched. Expert interviews were conducted, to gain insight in how the PVE method is perceived by policy-makers. The overall consensus is that PVE is a useful method of involving citizens. The PVE can be used by policy-makers as an advisory tool. Framing within PVE, is unwanted when testing the preferences of the citizens. However, it might be useful to emphasise the importance of certain projects. Therefore, it is argued that the use of framing should be an ethical consideration.

Despite the importance of the transition between the project and operation phase in Dutch building projects, both literature and practice show that the is in most cases this transition is not proceeding properly. Unstructured and incomplete two-dimensional documents are handed over and are inefficient and ineffective for use during the operation and maintenance of the building. This research investigates in how Building Information Modeling (BIM) can offer support in the improvement of the transition between the project and operation phase. The results show that BIM only working with BIM is not a solution for the issues that relate to the transition between the project and operation phase. BIM is a tool that can provide support but it is not a stand-alone solution for the structural problems in the building industry. If one wants to prevent the issues associated with the transition between to project and operation phase, the information management processes for which BIM is a supportive tool, need to be redesigned.

Police organisations wordwide struggle with the implementation of intelligence-led policing (ILP). This research aims to identify organisational factors that affect the state of implementation of ILP in the Dutch police force. From a multiple-case study research multiple factors have been identified that affect the functioning of ILP. These findings are integrated into a maturity model. By means of the maturity model the factors can be assessed, priorities for improvement can be determined and targeted improvement strategies can be derived. The findings can help police organisations to improve the implementation of ILP.

Maintaining infrastructure asset systems can be challenging for public authorities since we are living in a time where there is an increasing rate of deterioration of infrastructure assets such as tunnels, bridges and streets. This is due to the ageing and the increased use of these assets. As a result, some assets need additional maintenance measures, besides the regular maintenance, to keep them from failing. However, there is a limited budget making it impossible to invest simultaneously in each aging asset. As a solution, the asset manager can prioritize the numerous assets in order to know in which asset needs to be invested first. The sophistication of this prioritization strategy ranges from ‘observations’ via extended asset maintenance logs and logical reasoning down to more complex prioritization strategies which make use of risk assessment. Asset managers can use risk assessments to prioritize investments in the maintenance of their assets by assessing the risks of the assets’ failure. The risk of an asset failure can be defined as the probability of failure times the impact of failure. The higher the risk value attributed to the asset, the more critical the asset is assumed to be.

In practice, however, risk assessments of assets don’t always yield sufficient information to support a prioritization process and help decision makers to decide which investment in maintenance for which asset is necessary first. It appears that to be able to successfully conduct the risk assessment and prioritize maintenance, the asset manager must connect with two actor groups whose perspectives and interests have a big influence on the process which seeks to identify critical assets. One actor is the asset owner, whose interests towards assets are expressed at a strategic level and who speaks a non-technical, political language, has a long-term point of view and cares about social accountability. The service provider on the other hand speaks a technical, non-political language, has a short-term point of view and cares primarily about the functioning of the assets. So, these actor groups do not speak the same language, use different time perspectives and have diverging interests. Thus the asset manager has a challenging position and needs to translate content between these strategic and operational levels. This friction strongly affects the extent to which the asset manager can claim any degree of control over the process of identifying risks of all assets.

A literature review yielded many methods to identify the critical components of an object, which is necessary for determining the necessary maintenance measures to prevent risks. Nevertheless, no method in literature explains how asset managers can identify critical objects using risk assessments. However, such a method is required when an asset manager wants to prioritize objects of an infrastructure system in order to determine which object needs additional maintenance measures first to treat the current risks.

The objective of this research is therefore to develop a systematic process model for the asset manager to identify the critical public infrastructure objects that simultaneously complies with the interests of the three management levels involved in the asset management process: the asset owner, the asset manager and the service provider. This model is presented in an IDEF0 model, a type of process model, which shows the necessary activities, inputs, outputs, mechanisms and controls underlying the risk assessment process.